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Signaling bias is a feature of many G protein-coupled receptor (GPCR) targeting drugs with potential clinical implications. Whether it is therapeutically advantageous for a drug to be G protein biased or β-arrestin biased depends on the context of the signaling pathway. Here, we explored GPCR ligands that exhibit biased signaling to gain insights into scaffolds and pharmacophores that lead to bias. More specifically, we considered BiasDB, a database containing information about GPCR biased ligands, and focused our analysis on ligands which show either a G protein or β-arrestin bias. Five different machine learning models were trained on these ligands using 15 different sets of features. Molecular fragments which were important for training the models were analyzed. Two of these fragments (number of secondary amines and number of aromatic amines) were more prevalent in β-arrestin biased ligands. After training a random forest model on HierS scaffolds, we found five scaffolds, which demonstrated G protein or β-arrestin bias. We also conducted t-SNE clustering, observing correspondence between unsupervised and supervised machine learning methods. To increase the applicability of our work, we developed a web implementation of our models, which can predict bias based on user-provided SMILES, drug names, or PubChem CID. Our web implementation is available at: drugdiscovery.utep.edu/biasnet.

Microtubules are key players in several stages of the cell cycle and are also involved in the transportation of cellular organelles. Microtubules are polymerized by α/β tubulin dimers with a highly dynamic feature, especially at the plus ends of the microtubules. Therefore, understanding the interactions among tubulins is crucial for characterizing microtubule dynamics. Studying microtubule dynamics can help researchers make advances in the treatment of neurodegenerative diseases and cancer. In this study, we utilize a series of computational approaches to study the electrostatic interactions at the binding interfaces of tubulin monomers. Our study revealed that among all the four types of tubulin-tubulin binding modes, the electrostatic attractive interactions in the α/β tubulin binding are the strongest while the interactions of α/α tubulin binding in the longitudinal direction are the weakest. Our calculations explained that due to the electrostatic interactions, the tubulins always preferred to form α/β tubulin dimers. The interactions between two protofilaments are the weakest. Thus, the protofilaments are easily separated from each other. Furthermore, the important residues involved in the salt bridges at the binding interfaces of the tubulins are identified, which illustrates the details of the interactions in the microtubule. This study elucidates some mechanistic details of microtubule dynamics and also identifies important residues at the binding interfaces as potential drug targets for the inhibition of cancer cells.

Janus Kinase 3 (JAK3) plays a key role in the development, proliferation, and differentiation of various immune cells. It regulates gene expression by phosphorylation of Signal Transducers and Activators of Transcriptions (STATs) via the JAK/STAT pathway. Recently, we found a new JAK3 phosphorylation site, tyrosine 841 (Y841). The results showed that pY841 helps the kinase domain flip around the pseudo kinase domain, which may cause JAK3 conformational changes. It also reduces the size of the cleft between the N-lobe and the C-lobe of the JAK3 kinase domain. However, pY841 was found to enlarge the cleft when ATP/ADP was bound to the kinase. The increase in the cleft size suggested that pY841 enhanced the elasticity of the kinase domain. For unphosphorylated JAK3 (JAK3-Y841), the binding forces between the kinase domain and ATP or ADP were similar. After phosphorylation of Y841, JAK3-pY841 exhibited more salt bridges and hydrogen bonds between ATP and the kinase than between ADP and the kinase. Consequently, the electrostatic binding force between ATP and the kinase was higher than that between ADP and the kinase. The result was that compared to ADP, ATP was more attractive to JAK3 when Y841 was phosphorylated. Therefore, JAK3-pY841 tended to bind ATP rather than ADP. This work provides new insights into the role of phosphorylation in kinase activation and ATP hydrolysis and sheds light on the importance of understanding the molecular mechanisms that regulate the kinase function.

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